code: def visualize_class_separation(X, labels):
      _, (ax1, ax2) = plt.subplots(ncols=2)
      label_order = np.argsort(labels)
      ax1.imshow(
          pairwise_distances(X[label_order]), interpolation="nearest"
      )
      ax2.imshow(
          pairwise_distances(labels[label_order, None]),
          interpolation="nearest",
      )
  
file_path: metric-learn/examples/plot_sandwich.py
imports: import numpy
  from matplotlib import pyplot
  from sklearn.metrics import pairwise_distances
  from sklearn.neighbors import NearestNeighbors
  from metric_learn import LMNN, ITML_Supervised, LSML_Supervised, SDML_Supervised
label_desc: Use image node_id 2 for calling a global function with example usage: visualize_class_separation(X, labels) without return types